Please use this identifier to cite or link to this item: https://doi.org/10.15480/882.1741
This item is licensed with a CreativeCommons licence by-nc-nd/4.0
Publisher DOI: 10.1016/j.procir.2017.12.197
Title: Self-learning calculation for selective laser melting
Language: English
Authors: Rudolph, Jan-Peer 
Emmelmann, Claus 
Keywords: Calculation;Quotation costing;Self-learning;Selective laser melting (SLM);Additive manufacturing (AM)
Issue Date: 21-Mar-2018
Publisher: Elsevier
Source: Procedia CIRP (67): 185-190 (2018)
Journal or Series Name: Procedia CIRP 
Conference: 11th CIRP Conference on Intelligent Computation in Manufacturing Engineering, CIRP ICME '17 
Abstract (english): Selective laser melting (SLM) is increasingly used in the industrial production of metallic parts. This creates the need for an efficient and accurate quotation costing. The manufacturing costs of a part mainly result from the machine running time for coating and exposure. At the time of the offer calculation the final orientation of the part in the build chamber and the composition of the build job are typically not known. Addressing this need, this paper presents and evaluates different statistical based methods for an automated and self-learning calculation for SLM given a part’s CAD data.
URI: http://tubdok.tub.tuhh.de/handle/11420/1744
DOI: 10.15480/882.1741
ISSN: 2212-8271
Institute: Laser- und Anlagensystemtechnik G-2 
Type: (wissenschaftlicher) Artikel
Appears in Collections:Publications (tub.dok)

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